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DQ Asia Pacific 2008

29 - 30 April 2008 Crystal Palace, Luna Park Sydney, Australia 1 May 2008 Vibe Hotel North Sydney

Aligning strategy and tec hnology for improved data quality

Event Showguide Conference Dates and Times 29 - 30 April - 8.15am - 5.15pm Masterclasses, 1 May 2008 A & B - 9.30am - 12.30pm C & D - 1.30pm - 4.30pm

Diamond Sponsor:

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DAY ONE – Tuesday, 29 April 2008 8.15

Registration and refreshments

8.45

Chairperson’s opening remarks Suzette Bailey, Director, Sensory7

International keynote address Achieving IQ maturity: lessons learnt and best practices As the information quality discipline slowly matures through a turbulent DGROHVFHQFH PDQ\ RUJDQLVDWLRQV ÀQG WKHPVHOYHV XQDEOH WR VXFFHVVIXOO\ tackle the high costs of low data quality. However, a small but growing number of companies seem to have gotten it right and are enjoying sustained superior information quality results. What are they doing and how are they doing it? This presentation describes lessons learned and best practices developed in organisations that have achieved IQ maturity and success. C. Lwanga Yonke, Information Quality Expert and IAIDQ Advisor 9.00

'HOLYHULQJEXVLQHVVEHQHÀWVWKURXJKHIIHFWLYH information capture and management Developing a map of the functions of a business and its critical business tivities entifying the organisation’s intellectual assets and showing how they e deployed to undertake those business activities ‡ Aligning the business information strategy to best manage intellectual assets ‡ Implications of data integrity and quality for risk management, performance management and business intelligence James Price, Managing Director, Experience Matters 10.00

10.45

Extended exhibition break

11.15 Ensuring secure data transfer and data sharing Balancing information security with the need to share data with evant sources cilitating data transfer through databases ccessfully achieving data migration and merging similar data ssources sources ‡ Improving access and reducing corruption Craig Wright, Information Systems Manager, BDO Kendalls

Conference IBM Data Quality Program: A commonsense approach to data quality management ‡ How should an organisation get started with a data quality program? ‡ :KDWUROHGRHVGDWDTXDOLW\KDYHLQVLJQLÀFDQWGDWDLQWHJUDWLRQ projects like MDM, CDI or PIM? Data quality technology options: categories of data quality tools that H[LVWGDWDSURÀOLQJGDWDFOHDQVLQJHWF Who within an organisation should really be driving data quality programs? Patrick Connolly, Strategy and Product Marketing Manager, Data Quality for Information Integration Solutions, IBM 12.00

12.35

Extended exhibition lunch

1.35 Improving master data management and data quality Paul Ormonde-James, Head of Group Intelligence, MBF Australia Limited; and Australasian President, Data Warehousing Institute The three “Rs” of data quality: reliability, resilience and recoverability ‡ Applying availability standards to data centre facilities design (Uptime Institute and TIA942 standards) ‡ In-house or outsource: the business case for data centre hosting ‡ Designing resilient infrastructures to support data quality ‡ Architecting critical data systems for recoverability and testability in the event of data centre failure David McEwen, Director: Consulting, Roberts Weaver Group 3.05

Extended exhibition break and wine tasting by Pepper Tree Wines

Technology Stream Main Conference Room - Level 1

Strategy Stream Stream Room - Ground Floor

Chairperson: Suzette Bailey, Director, Sensory7

Chairperson: Geoffrey Vitlin, Director, Doll Martin Associates

Promoting storage capabilities through data warehousing ‡ A melting pot of organisational data: realising the value of arehouses in centralising data acking changes and identifying trends within data warehouses dopting appropriate technologies to manage warehouse data ‡ 8VLQJZDUHKRXVHGDWDWRVXSSRUWDQGLQÁXHQFHFUXFLDOEXVLQHVV decisions Bala Rasaratnam, Consulting and Innovation Manager, National Australia Bank 4.10

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2.20

After the break, the conference will break into two streams, one addressing technology, and the other, strategy. We invite you to attend the sessions that appeal most to your interest, and encourage you to move from one room to another to really gain the knowledge and information that applies to your individual situation.

3.35 Master data management and data integration ‡ Data quality, data duplication and multiple, disconnected systems aster data architectural patterns ata integration: data semantics stems of record, sources of truth, primary applications ‡ Data capture and propagation: orchestration and choreography Dr George Fernandez, Associate Professor, School of Computer Science and Information Technology, RMIT University

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Driving data quality as part of an ERP implementation: lessons learnt ‡ The importance of people and processes ‡ Dealing with the “nuts and bolts” of data conversion ‡ Aligning the functional needs of different departments ‡ Delivering local solutions in a global organisation 3.35

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Advancing the status of data quality within the organisation ‡ Viewing data as an asset rather than a commodity ‡ Moving from a reactive approach to a cultural strategy ‡ Creating a data culture to integrate data quality ‡ Programmes and services to optimise impact DQGHIÀFLHQF\ Ken Self, MRD Strategy Manager, Shell Australia 4.10

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5.15

Chairperson’s closing remarks and end of day one

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Suzette Bailey, Director, Sensory7

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Conference Conference DAY TWO – Wednesday, 30 April 2008 8.15

Registration and refreshments

8.45

Chairperson’s opening remarks Suzette Bailey, Director, Sensory7

International keynote address: The past, present, and future of data quality The last ten years have proven exciting for data quality practitioners, as more and more organisations have come to understand the critical importance of high-quality data. Many have made vast improvements, serving as role models for others. The next ten years promise to be even more exciting Leading organisations are coming to realise that data, just like capital and people, are assets that must be professionally managed and leveraged in the marketplace. One implication is that more data will be exposed to more mers in higher-stakes situations. In this presentation, the Data Doc looks backwards and forwards. He: mmarises progress to date cusses what “manage data assets” really means scribes some of the more important implications, and eculates on the future, ten years hence Dr Thomas C Redman Ph.D., President, Navesink Consulting Group; Co-Founder, IAIDQ 9.00

Panel discussion: Maintaining data integrity and accuracy This is your chance to gain an insight into the views of our data quality experts and how they deal with data integrity and accuracy in their workplace. Hear the thoughts and suggestions of experienced data practitioners on this crucial subject and then have the opportunity to pose your questions and gain a better understanding of the topic. 10.00

Craig Wright, Information Systems Manager, BDO Kendalls; Paul OrmondeJames, Head of Group Intelligence, MBF Australia Limited; and Australasian President, Data Warehousing Institute; Ken Self, MRD Strategy Manager, Shell Australia

11.15 Aligning technical and strategic objectives ‡ Examining the objectives of both sides of the data divide ‡ Prioritising key outcomes and establishing a united front to improve accuracy and frameworks ‡ Creating a centre of excellence that integrates technology and cultural perspectives ‡ Situating data quality in a business unit that allows better facilitation between IT and business Phil Considine, Data Management Consultant, PricewaterhouseCoopers Australia Auditing data to maintain integrity and derive business EHQHÀWV ‡ Ensuring availability of toolsets ‡ Identifying poor quality data and examining its cause ‡ Generating applicable results ‡ Applying audited data to organisational processes and projects Alex Kemeny, Independent contractor currently consulting to Allianz 12.00

12.35

Cleansing data to remove anomalous information and improve consistency ‡ Recognising the need for testing of both clean and corrupt data ‡ Making the case for automated data cleansing ‡ Utilising algorithms to closely analyse and cleanse data ‡ 'HWHUPLQLQJ¶ÀWIRUXVH·GDWD Matthew Allison, Data Quality Manager, Veda Advantage 1.35

2.20 &XVWRPHUGDWDTXDOLW\DQG&50V\VWHPVEHQHÀWV ‡ The value of customer information as a data resource ‡ Understanding customer data quality ‡ Assessing customer data quality ‡ $IUDPHZRUNIRUXQGHUVWDQGLQJ&50V\VWHPVEHQHÀWV Professor Graeme Shanks, School of Business Systems, University of Melbourne 3.05

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10.45

Extended exhibition lunch

Extended exhibition break and wine tasting by Pepper Tree Wines

Extended exhibition break

After the break, the conference will break into two streams, one addressing technology, and the other, strategy. We invite you to attend the sessions that appe appeal most to your interest, and encourage you to move from one room to another to really gain the knowledge and information that applies to your individual situation. Technology Stream Main Conference Room - Level 1

Strategy Stream Stream Room - Ground Floor

Chairperson: Suzette Bailey, Director, Sensory7

Chairperson: Robert Arnold, Director, Doll Martin Associates

The application of the audit framework for the purpose of reconciling a data warehouse with its source systems portunities and challenges for reconciling data between rce systems and a data warehouse requirements and logical design of the audit framework and reconciliation process sical implementation of an audit framework using SQL ver 2005 BI suite Zikic, Senior BI Developer, Australian Administration Services (AAS) Utilising data quality metrics to improve water quality orking with changing legislation veloping a national water information database for use by the eau of Meteorology ng data quality metrics to monitor and improve information hering and management ting metrics and monitored Key Performance Indicators (KPIs) to nage data quality at the point of data capture Grant Robinson, Information Auditor, Department of Water and Energy (NSW) and; Vice President Web Services, IAIDQ

4.55

Streams re-converge for wrap-up discussion

5.15

Chairperson’s closing remarks and end of conference

Suzette Bailey, Director, Sensory7

How to achieve better data quality though metadata and business rules ‡ Identifying and avoiding incorrect data tilising metadata to improve data quality nderstanding and implementing business rules aham Witt, Information Management Consultant, Ajilon Consultants 3.35

Advancing data governance to create improved data quality frameworks ‡ Ensuring sustained ownership of data quality to cultivate cohesive ideas and processes egotiating policies and legislation that affect data use and issemination GRSWLQJJRYHUQDQFHJURXSVWRGUDZRXWEXVLQHVVEHQHÀWVIURP data ‡ Creating and documenting data quality processes to create accountability and clarity Michael Axelsen, Director, Applied Insight Pty Ltd 4.10

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Mor ning Masterclasses

DAY THREE – Thursday, 1 May 2008 – Vibe Hotel North Sydney

Masterclass A

Masterclass B

9.30 - 12.30 Building and growing a successful IQ function

9.30 - 12.30 Data quality: what senior leaders need to know

Facilitator: C. Lwanga Yonke, Information Quality Expert and IAIDQ Advisor

Facilitator: Dr Thomas C Redman Ph.D., President, Navesink Consulting Group

About the masterclass: Successfully tackling the tough challenges caused by poor data quality often seems like an overwhelming and thankless task. Moreover, reover as awareness about the importance of information quality grows, information quality (IQ) practitioners are increasingly called to tackle a myriad of complex IQ problems.

About the masterclass: This session looks at data quality from the perspective of senior leadership. It begins with a discussion of the connections between data a quality and business performance, with an eye toward helping the senior leader assign data quality a proper priority. It then summarises FDQGLGDWHDSSURDFKHVIRULPSURYLQJGDWDTXDOLW\ÀQGLQJDQG À[LQJHUURUVWKDWKDYHDOUHDG\EHHQPDGHDQGSUHYHQWLQJQHZ ones at their sources.

To be successful in the short and long terms, the IQ practitioner must be equipped with a robust foundation deeply rooted in proven best practices and applicable to various IQ efforts including CDI, MDM, compliance, governance, data integration, business intelligence, etc. Drawing from lessons learnt at the frontline, this workshop describes the fundamental components of successful IQ functions and provides practical guidelines on getting started and UHPDLQLQJVXFFHVVIXO,WZLOOEHEHQHÀFLDOWRWKRVHLPSOHPHQWLQJ new information quality programs and to those seeking to re-energise or re-focus existing ones. Participants will leave with tangible solutions to many of their toughest IQ implementation challenges. About your masterclass leader: C. Lwanga Yonke is a seasoned information quality and information management expert and leader. He has successfully designed and implemented projects in multiple areas, including information quality, data governance, business intelligence, data warehousing and data architecture. His initial experience is in petroleum engineering and operations. $Q $64 &HUWLÀHG 4XDOLW\ (QJLQHHU /ZDQJD KROGV DQ 0%$ from California State University and a BS degree in petroleum engineering from the University of California at Berkeley. Lwanga is a founding member of the International Association for Information and Data Quality (IAIDQ) and currently serves as an Advisor to the IAIDQ Board. He is also a senior member of the American Society for Quality (ASQ), a member of the Society of Petroleum Engineers (SPE), and serves on the Boards RIVHYHUDOQRQSURÀWRUJDQLVDWLRQV

The emphasis is on elucidating the factors that senior leaders should consider as they work out how to bring the best of both approaches to bear inside their organisations. Finally, the workshop explores the ten habits of those with the best data, with special emphasis on the roles of senior leadership. About your masterclass leader: Thomas C. Redman, “the Data Doc,” is President of Navesink Consulting Group, which he IRXQGHG LQ   'U 5HGPDQ ZDV WKH ÀUVW WR H[WHQG TXDOLW\ principles to data and information and he is the leading inventor of practical techniques that help organisations improve. Prior to founding Navesink, Dr Redman established the AT&T Bell Laboratories Data Quality Lab in 1987 and led it until 1995. Dr Redman has written dozens of papers and three books. Data Quality: The Field Guide, is generally recognised as the leader. His fourth book, tentatively titled 7XUQLQJ'DWDWR3URÀWW is to be published by Harvard Business School Press in 2008. Published works: Data Quality: The Field Guide Dr Thomas C. Redman, Ph. D Boston, MA: Butterworth-Heinemann, 2001 Available for purchase at: http://tinyurl.com/28fecw Data Quality for the Information Age Dr Thomas C. Redman, Ph. D Norwood, MA: Artech House, 1996 Available for purchase at: http://tinyurl.com/2atmaa Data Quality: Management and Technology Dr Thomas C. Redman, Ph. D New York: Bantam Doubleday Dell, 1992 Available for purchase at: http://tinyurl.com/ypqtdl

Why is this event so relevant to you? 7KHLPSDFWRIGDWDTXDOLW\ZLWKLQRUJDQLVDWLRQVLVEHFRPLQJLQFUHDVLQJO\DSSDUHQWQRWRQO\WHFKQLFDOO\DQGÀQDQFLDOO\EXWDOVR culturally. Improving the quality of organisational data is quickly becoming a major area of expenditure and the challenge for practitioners is ensuring that the end results justify the costs and methodology involved. Ensuring quality from the point of capture, establishing sound technical platforms and creating a culture of data integrity at all levels of the organisation are paramount to achieve this, and maintaining the balance between these key areas is the main challenge facing data stewards.

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After Masterclasses After noon noon Masterclasses

DAY THREE – Thursday, 1 May 2008 – Vibe Hotel North Sydney

Masterclass C 1.30 - 4.30

Maintaining the currency and accuracy of content

Masterclass D 1.30 - 4.30

Breaking the limits of data quality Facilitators: Dr. Shazia Sadiq, Dr. Ke Deng, Prof. Xiaofang Zhou; Data and Knowledge Engineering Research Group, The University of Queensland

Fa Facilitator: Keith De La Rue, Knowledge Manager, Telstra M

About the maste masterclass: An interactive workshop, looking at maintaining content by using an integrated management program, based on the Telstra “KnowHow” model. ‡ A knowledge management toolkit approach to maintaining content ‡ Developing and applying a currency management strategy ‡ Setting up processes to identify when information is out of date ‡ Inviting user engagement to assist with improving content ‡*HWWLQJLWULJKWWKHÀUVWWLPHSUHYHQWLQJLQFRUUHFW information from getting online ‡ Building content management into standard business processes ‡7KHEHQHÀWVDQGULVNVRIDQRSHQSROLF\ About your masterclass leader: Keith De La Rue has worked in Knowledge Management at Telstra for the last seven years. He leads a team engaged in the transfer of product and solution knowledge to Telstra’s enterprise and business sales force. Keith is a committee member of the Melbourne Knowledge Management Leadership Forum, and is a regular speaker at conferences in Australia and overseas on a range of topics. He is also an experienced blogger, currently blogging at delarue. net.

About the masterclass: A fundamental issue in corporate data management initiatives is the measurement and subsequent DWWDLQPHQWRIGDWDTXDOLW\,QKHUHQWLQWKLVLVVXHLVWKHGHÀQLWLRQ of quality metrics, in other words, when is data “good enough?” It has become increasingly evident in the recent past due to the VFDOH DQG GLYHUVLW\ RI GDWD XVHUV WKDW GHÀQLQJ DQ\ DEVROXWH TXDOLW\ RI GDWD LV IXWLOH 'DWD TXDOLW\ PXVW EH GHÀQHG DV D function of data usage. This session will present state of the art in data quality research, highlighting key innovations brought forth by the database research community as well as from industry vendors from last several years. An analysis of the proposed techniques, tools and technologies will be presented in the light of data usage, thus providing a clear understanding of limitations and applicability. About your masterclass leaders: The session will be presented by a team of researchers from the University of Queensland. The team is part of the Data and Knowledge Engineering research group within the School of Information Technology and Electrical Engineering. Members of the team are leading various projects of data quality research both within the business as well DV VFLHQWLÀF GRPDLQ DQG DUH DOVR PDQDJLQJ WKH QDWLRQZLGH Australian Research Council Network on Enterprise Information Infrastructure.

Moving forward with an enterprise approach to knowledge, information and digital ta cultures

www kmaustralia com www.kmaustralia.com Relevant Ark Group Reports: '4$VLD3DFLÀFGHOHJDWHVUHFHLYHDVSHFLDOGHOHJDWHGLVFRXQW Data Quality – Trusted Data Across the Enterprise By Martin Spratt

SPECIAL NEW RELEASE 'DWD4XDOLW\7UXVWHG'DWD$FURVVWKH(QWHUSULVH² Author: Martin Spratt Price: AUD$695 $695 + GST AUD$400 + GST 5HVWRUHFRQÀGHQFHDQGWUXVWLQ\RXUGDWD7KLVUHSRUWUHYLHZVDUDQJHRIFXUUHQW'DWD4XDOLW\FKDOOHQJHVUHPHGLDWLRQVWUDWHJLHV technologies and case studies to help your organisation measure and improve Data Quality initiatives. 'DWD4XDOLW\DQG5HFRUGV0DQDJHPHQW(QKDQFLQJ7KH(QG8VHU([SHULHQFH² Author: Vanessa Osbourne Price: AUD$495 495 + GST AUD$295 + GST 'HVLJQHGVSHFLÀFDOO\WRKHOS\RXLGHQWLI\WKHULJKWV\VWHPVIRU\RXURUJDQLVDWLRQVHHKRZEHVWWRVWRUHDQGUHWULHYH\RXULQIRUPDWLR the integrity of the data that is so vital to your business and ensure the solution is embraced by end-users. If you would like information on these or any of the other wide range of Ark Group reports available, please visit: www.arkgroupaustralia.com.au/reports.htm or contact Laura Scully at [email protected].

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